Local metrics dashboards, buildable and configurable via MCP.
Then tell your LLM: “set up Tally from tally.monster.”
For your AI assistant
If you’re an AI assistant here to set Tally up: the app is its own MCP server. Register it, restart, and you can drive the running app by tool call.
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Make sure Tally is open.
It hosts a token-gated local API on 127.0.0.1:8787 that the MCP server forwards to. If it isn’t running, ask the human to launch it.
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Register tally mcp with your client.
The launch command is the installed Tally executable + the mcp arg. Find the executable for the human’s OS:
# macOS /Applications/Tally.app/Contents/MacOS/Tally # Windows %LOCALAPPDATA%\Tally\Tally.exe # Linux /usr/bin/tally # from the .deb; or the .AppImage path
Claude Code — swap the path for the OS above:
# macOS claude mcp add tally -- /Applications/Tally.app/Contents/MacOS/Tally mcp # Windows (PowerShell) claude mcp add tally -- "$env:LOCALAPPDATA\Tally\Tally.exe" mcp # Linux claude mcp add tally -- /usr/bin/tally mcp
Claude Desktop (macOS & Windows) — merge into its config, or just click Connect to Claude in the app. Config path: macOS ~/Library/Application Support/Claude/claude_desktop_config.json · Windows %APPDATA%\Claude\claude_desktop_config.json.
{ "mcpServers": { "tally": { "command": "<the executable path above>", "args": ["mcp"] } } }Cursor / Gemini CLI / any MCP host: add a stdio server with that executable as the command and args ["mcp"].
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Restart the client, then build.
Hosts read MCP config at launch — restart so the tally_* tools appear. Then: tally_search_collectors → tally_connect → tally_run → tally_create_dashboard + tally_add_chart. Nothing fits? tally_authoring_guide → tally_draft_collector → tally_save_collector. Reuse a signed collector before authoring one.